BackgroundAlthough mobile technologies such as smartphone apps are promising means for motivating people to adopt a healthier lifestyle (mHealth apps), previous studies have shown low adoption and continued use rates. Developing the means to address this issue requires further understanding of mHealth app nonusers and adoption processes. This study utilized a stage model approach based on the Precaution Adoption Process Model (PAPM), which proposes that people pass through qualitatively different motivational stages when adopting a behavior.ObjectiveTo establish a better understanding of between-stage transitions during app adoption, this study aimed to investigate the adoption process of nutrition and fitness app usage, and the sociodemographic and behavioral characteristics and decision-making style preferences of people at different adoption stages.MethodsParticipants (N=1236) were recruited onsite within the cohort study Konstanz Life Study. Use of mobile devices and nutrition and fitness apps, 5 behavior adoption stages of using nutrition and fitness apps, preference for intuition and deliberation in eating decision-making (E-PID), healthy eating style, sociodemographic variables, and body mass index (BMI) were assessed.ResultsAnalysis of the 5 behavior adoption stages showed that stage 1 (“unengaged”) was the most prevalent motivational stage for both nutrition and fitness app use, with half of the participants stating that they had never thought about using a nutrition app (52.41%, 533/1017), whereas less than one-third stated they had never thought about using a fitness app (29.25%, 301/1029). “Unengaged” nonusers (stage 1) showed a higher preference for an intuitive decision-making style when making eating decisions, whereas those who were already “acting” (stage 4) showed a greater preference for a deliberative decision-making style (F4,1012=21.83, P<.001). Furthermore, participants differed widely in their readiness to adopt nutrition and fitness apps, ranging from having “decided to” but not yet begun to act (stage 2; nutrition: 6.88%, 70/1017; fitness: 9.23%, 95/1029) to being “disengaged” following previous adoption (stage 5; nutrition: 13.77%, 140/1017; fitness: 15.06%, 155/1029).ConclusionsUsing a behavior stage model approach to describe the process of adopting nutrition and fitness apps revealed motivational stage differences between nonusers (being “unengaged,” having “decided not to act,” having “decided to act,” and being “disengaged”), which might contribute to a better understanding of the process of adopting mHealth apps and thus inform the future development of digital interventions. This study highlights that new user groups might be better reached by apps designed to address a more intuitive decision-making style.

Background Nutrition apps are effective in changing eating behavior and diet-related health risk factors. However, while they may curb growing overweight and obesity rates, widespread adoption is yet to be achieved. Hence, profound knowledge regarding factors motivating and hindering (long-term) nutrition app use is crucial for developing design guidelines aimed at supporting uptake and prolonged use of nutrition apps. Objective In this systematic review, we synthesized the literature on barriers to and facilitators for nutrition app use across disciplines including empirical qualitative and quantitative studies with current users, ex-users, and nonusers of nutrition apps. Methods A systematic literature search including 6 databases (PubMed, Web of Science, PsychINFO, PSYNDEX, PsycArticles, and SPORTDiscus) as well as backward and forward citation search was conducted. Search strategy, inclusion and exclusion criteria, and the planned data extraction process were preregistered. All empirical qualitative and quantitative studies published in German or English were eligible for inclusion if they examined adolescents (aged 13-18) or adults who were either current users, ex-users, and nonusers of nutrition apps. Based on qualitative content analysis, extracted individual barriers and facilitators were grouped into categories. Results A total of 28 publications were identified as eligible. A framework with a 3-level hierarchy was designed which grouped 328 individual barriers and facilitators into 23 subcategories, 12 categories, and 4 clusters that focus on either the individual user (goal setting and goal striving, motivation, routines, lack of awareness of knowledge), different aspects of the app and the smartphone (features, usability of the app or food database, technical issues, data security, accuracy/trustworthiness, costs), positive and negative outcomes of nutrition app use, or interactions between the user and their social environment. Conclusions The resulting conceptual framework underlines a pronounced diversity of reasons for (not) using nutrition apps, indicating that there is no “one-size-fits-all” approach for uptake and prolonged use of nutrition apps. Hence, tailoring nutrition apps to needs of specific user groups seems promising for increasing engagement.

Research suggests that “healthy” food choices such as eating fruits and vegetables have not only physical but also mental health benefits and might be a long-term investment in future well-being. This view contrasts with the belief that high-caloric foods taste better, make us happy, and alleviate a negative mood. To provide a more comprehensive assessment of food choice and well-being, we investigated in-the-moment eating happiness by assessing complete, real life dietary behaviour across eight days using smartphone-based ecological momentary assessment. Three main findings emerged: First, of 14 different main food categories, vegetables consumption contributed the largest share to eating happiness measured across eight days. Second, sweets on average provided comparable induced eating happiness to “healthy” food choices such as fruits or vegetables. Third, dinner elicited comparable eating happiness to snacking. These findings are discussed within the “food as health” and “food as well-being” perspectives on eating behaviour.

Background Dietary guidelines typically specify rather complex goals and indicators for healthy food choices, such as nutrient and energy content patterns. However, translating these complex goals into practice in real life is often a major obstacle for many people. The present studies propose an intervention strategy for boosting healthy food choices by prompting consumers at a meaningful moment with a simple behavioural trigger, that is to eat a colourful lunch. Effectivity and feasibility of this intervention strategy were tested in two laboratory experiments and one real-life, smartphone-based Ecological Momentary Intervention. Methods In Studies 1 and 2, 83 / 42 participants self-served four meals (colourful, typical, healthy, and low-calorie) / three meals (colourful, typical, and varied) from a Fake Food Buffet. In Study 3, 80 participants recorded images of 1,210 lunch meals over a period of 3 weeks using mobile visual food recording. In the second week, participants additionally received a daily smartphone prompt to eat a colourful lunch. In all studies, participants were asked to rate the prompts’ feasibility. Results Prompting participants to eat a colourful meal increased the proportion of healthy foods consumed compared to typical meals in all three studies. In Studies 1 and 2, colourful meals contained more fruit and vegetables, while in Study 3 the prompt increased vegetable consumption. Furthermore, participants evaluated colourful meals to be the tastiest (Study 1) and most pleasant, and reported that the prompt was easy to follow and act upon. Conclusions Results suggest that prompting individuals to eat colourful meals is a promising strategy to facilitate healthy food choices in daily life. Trial registration German Clinical Trials Register, DRKS00017552 (Study 3; retrospectively registered on 24 th June 2019). Electronic supplementary material The online version of this article (10.1186/s12889-019-7306-z) contains supplementary material, which is available to authorized users.

No abstract